DeePMD-kit v2: A software package for deep potential models
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material scien...
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| Veröffentlicht in: | The Journal of chemical physics Jg. 159; H. 5 |
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
07.08.2023
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| ISSN: | 1089-7690, 1089-7690 |
| Online-Zugang: | Weitere Angaben |
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| Abstract | DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments. |
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| AbstractList | DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments. DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments. |
| Author | Shi, Shaochen Yang, Jiabin Huang, Jiameng Zhang, Duo Li, Yifan Muraoka, Koki Zhang, Yuzhi Liang, Wenshuo Ye, Haotian York, Darrin M Bore, Sigbjørn Løland Tisi, Davide Yao, Sikai Han, Jiequn Ding, Ye Rynik, Marián Liu, Jie Wentzcovitch, Renata Chen, Yixiao Zhang, Jingchao Wang, Yingze Jia, Weile E, Weinan Tuo, Ping Lin, Yinnian Mo, Pinghui Xia, Yu Wang, Yibo Cai, Chun Chang, Junhan Zeng, Jinzhe Singh, Anurag Kumar Car, Roberto Goodall, Rhys E A Zhang, Linfeng Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Li, Zeyu Wang, Bo Yuan, Fengbo Li, Ziyao Lu, Denghui Huang, Li'ang Bao, Han Wang, Han Zeng, Qiyu |
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0009-0008-4381-0544 surname: Li fullname: Li, Zeyu organization: Yuanpei College, Peking University, Beijing 100871, People's Republic of China – sequence: 6 givenname: Yixiao orcidid: 0000-0001-8201-5887 surname: Chen fullname: Chen, Yixiao organization: Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08540, USA – sequence: 7 givenname: Marián orcidid: 0009-0006-5745-1525 surname: Rynik fullname: Rynik, Marián organization: Department of Experimental Physics, Comenius University, Mlynská Dolina F2, 842 48 Bratislava, Slovakia – sequence: 8 givenname: Li'ang orcidid: 0009-0001-4185-9677 surname: Huang fullname: Huang, Li'ang organization: Center for Quantum Information, Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing 100084, People's Republic of China – sequence: 9 givenname: Ziyao orcidid: 0000-0002-9071-2516 surname: Li fullname: Li, Ziyao organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 10 givenname: Shaochen orcidid: 0000-0003-3457-403X surname: Shi fullname: Shi, Shaochen organization: ByteDance Research, Zhonghang Plaza, No. 43, North 3rd Ring West Road, Haidian District, Beijing, People's Republic of China – sequence: 11 givenname: Yingze surname: Wang fullname: Wang, Yingze organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 12 givenname: Haotian orcidid: 0009-0005-8486-0626 surname: Ye fullname: Ye, Haotian organization: Yuanpei College, Peking University, Beijing 100871, People's Republic of China – sequence: 13 givenname: Ping orcidid: 0000-0002-6477-5900 surname: Tuo fullname: Tuo, Ping organization: AI for Science Institute, Beijing 100080, People's Republic of China – sequence: 14 givenname: Jiabin surname: Yang fullname: Yang, Jiabin organization: Baidu, Inc., Beijing, People's Republic of China – sequence: 15 givenname: Ye orcidid: 0009-0005-1986-2879 surname: Ding fullname: Ding, Ye organization: Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA – sequence: 16 givenname: Yifan orcidid: 0000-0003-3217-0592 surname: Li fullname: Li, Yifan organization: Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA – sequence: 17 givenname: Davide orcidid: 0000-0001-7229-6101 surname: Tisi fullname: Tisi, Davide organization: Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA – sequence: 18 givenname: Qiyu orcidid: 0009-0004-2304-0213 surname: Zeng fullname: Zeng, Qiyu organization: Department of Physics, National University of Defense Technology, Changsha, Hunan 410073, People's Republic of China – sequence: 19 givenname: Han orcidid: 0000-0003-3490-0974 surname: Bao fullname: Bao, Han organization: AI for Science Institute, Beijing 100080, People's Republic of China – sequence: 20 givenname: Yu orcidid: 0009-0004-9087-9414 surname: Xia fullname: Xia, Yu organization: ByteDance Research, Zhonghang Plaza, No. 43, North 3rd Ring West Road, Haidian District, Beijing, People's Republic of China – sequence: 21 givenname: Jiameng orcidid: 0009-0002-9701-8145 surname: Huang fullname: Huang, Jiameng organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 22 givenname: Koki orcidid: 0000-0003-1830-7978 surname: Muraoka fullname: Muraoka, Koki organization: Department of Chemical System Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan – sequence: 23 givenname: Yibo orcidid: 0009-0001-3921-4415 surname: Wang fullname: Wang, Yibo organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 24 givenname: Junhan orcidid: 0000-0003-3195-0773 surname: Chang fullname: Chang, Junhan organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 25 givenname: Fengbo orcidid: 0009-0002-3949-8785 surname: Yuan fullname: Yuan, Fengbo organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 26 givenname: Sigbjørn Løland orcidid: 0000-0002-8620-4885 surname: Bore fullname: Bore, Sigbjørn Løland organization: Hylleraas Centre for Quantum Molecular Sciences and Department of Chemistry, University of Oslo, P.O. Box 1033 Blindern, 0315 Oslo, Norway – sequence: 27 givenname: Chun orcidid: 0000-0001-6242-0439 surname: Cai fullname: Cai, Chun organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 28 givenname: Yinnian orcidid: 0009-0008-1709-7239 surname: Lin fullname: Lin, Yinnian organization: Wangxuan Institute of Computer Technology, Peking University, Beijing 100871, People's Republic of China – sequence: 29 givenname: Bo orcidid: 0000-0002-2733-9253 surname: Wang fullname: Wang, Bo organization: Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Key Laboratory of Green Chemistry and Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, People's Republic of China – sequence: 30 givenname: Jiayan orcidid: 0000-0001-9897-5778 surname: Xu fullname: Xu, Jiayan organization: School of Chemistry and Chemical Engineering, Queen's University Belfast, Belfast BT9 5AG, United Kingdom – sequence: 31 givenname: Jia-Xin orcidid: 0000-0002-3471-4728 surname: Zhu fullname: Zhu, Jia-Xin organization: State Key Laboratory of Physical Chemistry of Solid Surfaces, iChEM, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China – sequence: 32 givenname: Chenxing orcidid: 0000-0003-4116-6851 surname: Luo fullname: Luo, Chenxing organization: Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, USA – sequence: 33 givenname: Yuzhi orcidid: 0000-0002-5841-1107 surname: Zhang fullname: Zhang, Yuzhi organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 34 givenname: Rhys E A orcidid: 0000-0002-6589-1700 surname: Goodall fullname: Goodall, Rhys E A organization: Independent Researcher, London, United Kingdom – sequence: 35 givenname: Wenshuo orcidid: 0000-0003-0646-8803 surname: Liang fullname: Liang, Wenshuo organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 36 givenname: Anurag Kumar orcidid: 0009-0001-6255-5867 surname: Singh fullname: Singh, Anurag Kumar organization: Department of Data Science, Indian Institute of Technology, Palakkad, Kerala, India – sequence: 37 givenname: Sikai orcidid: 0009-0009-3429-0476 surname: Yao fullname: Yao, Sikai organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 38 givenname: Jingchao orcidid: 0000-0001-5289-6062 surname: Zhang fullname: Zhang, Jingchao organization: NVIDIA AI Technology Center (NVAITC), Santa Clara, California 95051, USA – sequence: 39 givenname: Renata orcidid: 0000-0001-5663-9426 surname: Wentzcovitch fullname: Wentzcovitch, Renata organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 40 givenname: Jiequn orcidid: 0000-0002-3553-7313 surname: Han fullname: Han, Jiequn organization: Center for Computational Mathematics, Flatiron Institute, New York, New York 10010, USA – sequence: 41 givenname: Jie orcidid: 0000-0001-8663-3551 surname: Liu fullname: Liu, Jie organization: College of Electrical and Information Engineering, Hunan University, Changsha, People's Republic of China – sequence: 42 givenname: Weile orcidid: 0000-0001-8539-8326 surname: Jia fullname: Jia, Weile organization: AI for Science Institute, Beijing 100080, People's Republic of China – sequence: 43 givenname: Darrin M orcidid: 0000-0002-9193-7055 surname: York fullname: York, Darrin M organization: Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA – sequence: 44 givenname: Weinan orcidid: 0000-0003-0272-9500 surname: E fullname: E, Weinan organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 45 givenname: Roberto orcidid: 0000-0001-5243-2647 surname: Car fullname: Car, Roberto organization: Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA – sequence: 46 givenname: Linfeng orcidid: 0000-0002-8470-5846 surname: Zhang fullname: Zhang, Linfeng organization: DP Technology, Beijing 100080, People's Republic of China – sequence: 47 givenname: Han orcidid: 0000-0001-5623-1148 surname: Wang fullname: Wang, Han organization: HEDPS, CAPT, College of Engineering, Peking University, Beijing 100871, People's Republic of China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37526163$$D View this record in MEDLINE/PubMed |
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